Stem cells, embryonic and adult, represent the foundation for regenerative medicine. Their unique ability to undergo self-renewal balanced with the capacity to generate numerous differentiated cell types promises to revolutionize therapy of degenerative disorders. A central challenge to their widespread translational use is the identification of environmental cues and genetic regulatory networks that govern the self-renewal and directed differentiation of stem cells into a tissue of interest. Identification of the underlying gene regulatory circuitry at work is a key step for directing stem cell differentiation. Moreover, the ability to modulate and monitor stem cells to test predicted gene regulatory network relationships is a necessary step in evaluating plausible, reproducible and efficient methods for the genetic guidance of differentiation. Here we propose to adapt our existing microtechnology platform for dynamic imaging of multiplexed microenvironments to understanding and evaluating the role of gene regulatory networks in stem cell differentiation. The introduction of known genetic activators combined with cell lineage reporters provides a unique readout for the potential use of genetic methods to guide stem cell differentiation. Through the viral expression of exogenous genetic factors and monitoring of fluorescence reporters we will evaluate gene regulatory networks underlying the differentiation of murine embryonic stem cells into pancreatic endoderm, tooth and heart valve tissue as part of the SysCODE consortium. Furthermore, the use of microtechnology tools provide microenvironments that can be exposed to a variety of independent perturbations and the response monitored with high temporal and spatial resolution, permitting the evaluation of many genetic inputs along a specific cellular differentiation pathway. The moderate throughput nature of our technology platform in combination with the generation of potential gene regulatory networks through the SysCODE consortium represent a powerful testbed for the evaluation of network predictions and ultimately potential targets for developing in vitro methods and therapies for tissue regeneration and organogenesis.